ClovenDoug
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Browse files- README.md +228 -0
- added_tokens.json +4 -0
- config.json +135 -0
- model.safetensors +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +76 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
README.md
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---
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library_name: span-marker
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tags:
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- span-marker
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- token-classification
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- ner
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- named-entity-recognition
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- generated_from_span_marker_trainer
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metrics:
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- precision
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- recall
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- f1
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widget:
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- text: 'In the 2017 publication "The Routledge Handbook of Collective Intentionality",
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edited by Kirk Ludwig and Marija Jankovic, and released by Routledge, leading
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scholars explored the complex concept of collective intentionality and its implications
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for various disciplines, including philosophy, cognitive science, and social theory
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+
. A thought-provoking 2015 article titled "The Uncivilization Thesis: A Critique"
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by Megan Gittins, published in Environmental Ethics, offered a critical examination
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of the controversial "uncivilization thesis" and its implications for our understanding
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of the relationship between civilization and environmental sustainability.'
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- text: In the "The Selfish Gene", renowned biologist Richard Dawkins introduced the
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revolutionary concept of the "selfish gene" in 1976, published by Oxford University
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Press . This influential work challenged traditional views of evolution and sparked
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widespread discussions about the nature of altruism and cooperation . Fans of
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science writing might appreciate "A Short History of Nearly Everything" by Bill
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Bryson, a captivating exploration of the vast realms of scientific knowledge published
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by Broadway Books in 2003.
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+
- text: '"The Pragmatic Turn" (2020, University of Pennsylvania Press) provides key
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+
insights into pragmatist philosophy, edited by John J. Stuhr . For provocative
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+
science, try "Introducing Consciousness", Alex Westrin and Vidyut Lokhande''s
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+
2018 work published via Icon Books, challenging dominant models of self-awareness.'
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+
- text: Have you read "The Selfish Gene" by Richard Dawkins? Published in 1976 by
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+
Oxford University Press, this seminal work introduced the gene-centric view of
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evolution and proposed the controversial concept of the "extended phenotype ."
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+
Dawkins' ideas sparked intense debates and influenced diverse fields like evolutionary
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biology, psychology, and memetics . Daniel C. Dennett's "Darwin's Dangerous Idea"
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(1995, Simon & Schuster) is another must-read that explores the far-reaching implications
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of evolutionary theory, from the origins of life to the nature of human consciousness
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and free will.
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- text: '"The Sociology of Philosophies", an insightful book penned by Randall Collins
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and published in 1998 by Harvard University Press, examined the social factors
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that influence the development and trajectory of philosophical thought throughout
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history . Collins'' analysis shed light on how philosophical ideas are shaped
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by the broader cultural, political, and intellectual contexts in which they emerge
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. In a 2012 article from Philosophy of the Social Sciences, titled "The Relevance
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of the Sociology of Philosophy", Isaac Reed further expounded on the importance
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of this interdisciplinary approach, highlighting its potential to deepen our understanding
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of the dynamics that shape human knowledge and inquiry.'
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pipeline_tag: token-classification
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model-index:
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- name: SpanMarker
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results:
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- task:
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type: token-classification
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name: Named Entity Recognition
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dataset:
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name: Unknown
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type: unknown
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split: eval
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metrics:
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- type: f1
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value: 0.0
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name: F1
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- type: precision
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value: 0.0
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name: Precision
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- type: recall
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value: 0.0
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name: Recall
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---
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# SpanMarker
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition.
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## Model Details
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### Model Description
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- **Model Type:** SpanMarker
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<!-- - **Encoder:** [Unknown](https://huggingface.co/unknown) -->
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- **Maximum Sequence Length:** 512 tokens
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- **Maximum Entity Length:** 16 words
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER)
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- **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf)
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### Model Labels
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| Label | Examples |
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|:-----------------|:----------------------------------------------------------------------------------------------------------------------------------------------|
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| person | "Barney Glaser", "Malcolm Gladwell", "Charles Duhigg" |
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| publication_date | "2000", "1967", "2018" |
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| publisher | "Little , Brown and Company", "Sociology Press", "Avery" |
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| work_of_art | "`` The Tipping Point : How Little Things Can Make a Big Difference ''", "`` The Power of Habit ''", "`` The Discovery of Grounded Theory ''" |
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## Evaluation
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### Metrics
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| Label | Precision | Recall | F1 |
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|:-----------------|:----------|:-------|:----|
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| **all** | 0.0 | 0.0 | 0.0 |
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| person | 0.0 | 0.0 | 0.0 |
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| publication_date | 0.0 | 0.0 | 0.0 |
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| publisher | 0.0 | 0.0 | 0.0 |
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| work_of_art | 0.0 | 0.0 | 0.0 |
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## Uses
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### Direct Use for Inference
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```python
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from span_marker import SpanMarkerModel
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# Download from the 🤗 Hub
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model = SpanMarkerModel.from_pretrained("span_marker_model_id")
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# Run inference
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entities = model.predict("\"The Pragmatic Turn\" (2020, University of Pennsylvania Press) provides key insights into pragmatist philosophy, edited by John J. Stuhr . For provocative science, try \"Introducing Consciousness\", Alex Westrin and Vidyut Lokhande's 2018 work published via Icon Books, challenging dominant models of self-awareness.")
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```
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### Downstream Use
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You can finetune this model on your own dataset.
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<details><summary>Click to expand</summary>
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```python
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from span_marker import SpanMarkerModel, Trainer
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# Download from the 🤗 Hub
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model = SpanMarkerModel.from_pretrained("span_marker_model_id")
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# Specify a Dataset with "tokens" and "ner_tag" columns
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dataset = load_dataset("conll2003") # For example CoNLL2003
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# Initialize a Trainer using the pretrained model & dataset
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trainer = Trainer(
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model=model,
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train_dataset=dataset["train"],
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eval_dataset=dataset["validation"],
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)
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trainer.train()
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trainer.save_model("span_marker_model_id-finetuned")
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```
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</details>
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<!--
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### Out-of-Scope Use
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*List how the model may foreseeably be misused and address what users ought not to do with the model.*
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-->
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<!--
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## Bias, Risks and Limitations
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*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
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-->
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<!--
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### Recommendations
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*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
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-->
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## Training Details
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### Training Set Metrics
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| Training set | Min | Median | Max |
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|:----------------------|:----|:---------|:----|
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| Sentence length | 47 | 104.6034 | 200 |
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| Entities per sentence | 3 | 4.0036 | 5 |
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### Training Hyperparameters
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training Results
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| Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy |
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|:-----:|:----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:|
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| 1.0 | 563 | 0.0206 | 0.0 | 0.0 | 0.0 | 0.8513 |
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| 2.0 | 1126 | 0.0173 | 0.0 | 0.0 | 0.0 | 0.8513 |
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| 3.0 | 1689 | 0.0162 | 0.0 | 0.0 | 0.0 | 0.8513 |
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### Framework Versions
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- Python: 3.10.13
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- SpanMarker: 1.5.1.dev
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- Transformers: 4.39.3
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- PyTorch: 2.1.2
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- Datasets: 2.16.0
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- Tokenizers: 0.15.0
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## Citation
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### BibTeX
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```
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@software{Aarsen_SpanMarker,
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author = {Aarsen, Tom},
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license = {Apache-2.0},
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title = {{SpanMarker for Named Entity Recognition}},
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url = {https://github.com/tomaarsen/SpanMarkerNER}
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}
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```
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<!--
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## Glossary
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*Clearly define terms in order to be accessible across audiences.*
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-->
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<!--
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## Model Card Authors
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*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
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-->
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<!--
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## Model Card Contact
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*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
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-->
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added_tokens.json
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{
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"<end>": 30523,
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"<start>": 30522
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}
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config.json
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{
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"architectures": [
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"SpanMarkerModel"
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],
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"encoder": {
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"_name_or_path": "prajjwal1/bert-tiny",
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"add_cross_attention": false,
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"architectures": null,
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"attention_probs_dropout_prob": 0.1,
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"bad_words_ids": null,
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"begin_suppress_tokens": null,
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"bos_token_id": null,
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"chunk_size_feed_forward": 0,
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"classifier_dropout": null,
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"cross_attention_hidden_size": null,
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"decoder_start_token_id": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": null,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 128,
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"id2label": {
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"0": "O",
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"1": "B-publication_date",
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"2": "I-publication_date",
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"3": "B-person",
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"4": "I-person",
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"5": "B-work_of_art",
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"6": "I-work_of_art",
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"7": "B-publisher",
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"8": "I-publisher"
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},
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"initializer_range": 0.02,
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"intermediate_size": 512,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"B-person": 3,
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"B-publication_date": 1,
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"B-publisher": 7,
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"B-work_of_art": 5,
|
49 |
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|
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|
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 17556588
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special_tokens_map.json
ADDED
@@ -0,0 +1,7 @@
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|
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|
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tokenizer.json
ADDED
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tokenizer_config.json
ADDED
@@ -0,0 +1,76 @@
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
76 |
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training_args.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:0f65b5f0ced4bfab93e9dd4c9c08b783de27ffe4bdba0712ee91f763e2c1ee80
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size 4920
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vocab.txt
ADDED
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|
|